How Nvidia became the driving force behind the AI revolution
Two books chart the rise of the chipmaker via its ‘benevolent dictator’ Jensen Huang and an early gamble on deep learning
Jensen Huang has often tried to explain what his business does. Yet, even after Nvidia became the world’s most valuable company, many people can barely pronounce its name right, let alone understand how an outfit that started out making graphics chips for video games ended up powering a revolution in artificial intelligence and writing a new chapter in computing history.
One of Nvidia’s more eye-catching attempts at corporate self-explanation came at a company event back in 2008. It enlisted the hosts of pop-science TV show MythBusters to demonstrate the difference between its graphics processing units (the GPUs that today form the silicon backbone of OpenAI and its ilk) and the central processing units made by its rival Intel.
It involved paintball guns. If traditional CPUs are like a single gun popping blobs of paint to make a simple smiley face, GPUs are a giant 1,100-barrel paintball machine that splats out a pixelated Mona Lisa in a fraction of a second. While CPUs work one task at a time, Nvidia’s GPUs can handle multiple calculations all at once.
This “parallel processing” is ideal for accelerating tasks such as rendering graphics in video games — and crunching an entire internet’s worth of data to create the AI system behind ChatGPT. It was that capability to enable the AI revolution that sent Silicon Valley giants scrambling to spend billions on Nvidia’s chips and investors piling into the company’s stock, propelling its market capitalisation to $3tn. By 2024 Nvidia had become, as Goldman Sachs put it, “the most important stock on earth”.
Most of the stock market gains — the shares rose roughly 50,000 per cent between the MythBusters stunt and their peak this January — were made following ChatGPT’s launch in 2022. That may explain why nobody had written a book about Nvidia before — and why two corporate biographies have now been published within five months.
Tae Kim’s diligent and thorough The Nvidia Way arrived first. But it is Stephen Witt’s The Thinking Machine, out this month, that provides the richer and more accessible account of Nvidia’s 30-year journey from Silicon Valley also-ran to AI behemoth some of whose hardware, he writes, ranks alongside Turing’s Colossus and the Apple II as “one of the most important computers ever built”.
It was the capability of Nvidia’s GPUs to enable the AI revolution that sent Silicon Valley giants scrambling to spend billions on its chips and investors piling into its stock
Both books centre their narrative on Nvidia’s co-founder and chief executive Huang, dubbed “Professor Jensen” by Kim. In a tech industry that venerates founders, Huang is the last of Silicon Valley’s pre-dotcom chief executives still running his own company. His tech icon status is only burnished by his long battle against doubters and, now, ungodly wealth.
Portrayed as a benevolent dictator with a penchant for aphorisms and yelling at underlings, Huang has lived every entrepreneurial trope: the rags to riches immigrant; several near-death experiences; the David vs Goliath battle; and the unlikely gamble that is now finally paying off.
“What mattered at Nvidia wasn’t profits or revenues,” writes Witt, a Los Angeles-based journalist and author whose last book explained how online piracy roiled the music industry. “What mattered was the obsessive chief executive and his crazy long-shot bets. Either you believed in him or you didn’t.”
Working in the semiconductor industry meant the Taiwanese-American spent much of his career out of the spotlight, as attention focused on the tech founders whose products were familiar first-hand to billions of people.
Yet Huang — who now argues Nvidia makes not merely chips but “AI factories” — shares many attributes with Silicon Valley’s best-known names. He has the raw intelligence of Google’s Larry Page and Sergey Brin; Elon Musk’s long-term thinking; Steve Jobs’ knack for predicting what people want before they know it themselves; Mark Zuckerberg’s ability to pivot a multibillion-dollar company on a dime; Jeff Bezos’ underdog mentality. Beyond such Olympian tech-bro traits, both books also highlight Huang’s more everyday human qualities — focus, workaholism, luck and a dry sense of humour.
Lately, Huang has leaned into his newfound celebrity. At Nvidia’s annual GTC conference for AI developers last month, clad in his trademark leather jacket — the product of a makeover instigated by his wife and daughter — Huang wielded a cannon firing T-shirts into the crowd that packed out an ice hockey stadium to hear his one-man, two-hour keynote.
The conference also featured “Nvidia Breakfast Bytes”, a branded meal from restaurant chain Denny’s. The teenage Huang, who moved to the US aged nine, washed dishes at a Portland, Oregon branch of the all-American diner. Bottomless coffees at a Silicon Valley Denny’s later fuelled Nvidia’s three founders as they hatched their plan to take on Intel, then the dominant force in semiconductors.
The two authors, who both confess to being video game addicts, each chart Nvidia’s rocky journey from Denny’s to creating, as Witt puts it, “the world’s most coveted microchip”. (By late 2023, two of the world’s richest men — Musk and Larry Ellison, co-founder of software giant Oracle — were begging Huang to sell them more of his chips over sushi at Nobu in Palo Alto.)
The framing of Kim’s account centres on Huang’s management maxims — such as working as if the company was always “30 days from going out of business”, which at one point it was — and Nvidia’s unusually flat corporate structure. More than 30 managers report to the chief executive, who obsessively fights bureaucracy. Instead of hiding in a corner office, Huang stalks Nvidia’s headquarters, able to jump into deep technical conversations with almost any of its 36,000 employees. Those who ramble nervously in response are told “LUA”: “Listen to the question. Understand the question. Answer the question”.
Even when Jensen erupts into one of his infamous shouting sessions, failing staff rarely get fired, as they might at Musk’s X or Tesla. “No one loses alone” is another Huang motto. “I’ve been afraid of Jensen sometimes,” one employee tells Witt. “But I also know that he loves me.”
Where Kim — a veteran Nvidia follower, first as an investment analyst, now as business journalist — is more into the hardware and corporate culture, Witt prefers people. He tells his story through an engaging cast of Valley supernerds: the misfit academics, game designers and programming geniuses who helped Nvidia survive its early failures to seize what Huang identified early as a “once in a lifetime opportunity” in AI. These vivid characters help the reader navigate the chewier technical details about the unlikely marriage of parallel processing and computers that could “think”.
The key to that trillion-dollar combination actually lies not in Nvidia’s hardware but its Cuda software, a project which began in the mid-2000s to “turn your graphics card into a supercomputer”. This revolutionary idea would become the most powerful shift in how chips work for decades.
When Cuda began, Witt reckons Huang’s gambles had lost more than they’d won. Its stock languished and Nvidia was targeted by activist investors, who pushed Huang to stick to gaming instead of a quixotic mission to use parallel processors for scientific discovery or mining exploration. But Huang refused to ditch Cuda, even when his peers in the chip industry thought he was on to another loser. “It was the bet that made Jensen Jensen,” writes Witt. “It was the gamble that set him apart.”
In 2013, Huang sent a Friday-night email to the entire company telling them Nvidia was no longer in the graphics business and was going all in on deep learning
The breakthrough came with the 2012 introduction of the AlexNet image classification system, whose creators used an Nvidia GPU to do in 30 seconds what would have taken an hour on a standard Intel machine. As buzz about this new approach to AI rippled through Silicon Valley, Huang, who had just turned 50, sent a Friday-night email to the entire company telling them Nvidia was no longer in the graphics business and was going all in on deep learning. A decade later, he was proved very right.
Though Witt does not gloss over the science bits of transformer architectures and FinFET transistors, there are some odd omissions, even if these help sustain The Thinking Machine’s brisk pace. An early-2000s brush with what the US financial regulator called “accounting misconduct”, which contributed to its prolonged share-price slump, is dealt with in half a page. The book also barely scratches the surface of Nvidia’s complex relationship with China, the risks of its overwhelming dependence on Taiwanese manufacturing and its challenges in wrangling the US government’s chip export controls.
But if Witt downplays geopolitics, so too, apparently, does Huang. In the book’s most alarming revelation, the author claims that Nvidia has done “no contingency planning” for a Chinese invasion of Taiwan, following an edict from Huang. “I don’t want [Nvidia’s logistics chief] spending one brain cell on trying to mitigate that, because it’s impossible for her to do so,” he is quoted by Witt as saying.
Witt is more worried about world war three being fought against robots than China. At the same time as marvelling at Nvidia’s technology, the author says his anxiety about AI and its threat to humanity — first writers, then the world? — motivated the book. Yet when he challenges Huang on it, the CEO replies: “I’m so tired of this question.”
“They were building the Manhattan Project of computer science,” Witt writes, “but when I questioned Nvidia executives about the wisdom of unleashing such power, they looked at me like I was questioning the utility of the washing machine.”
Kim ends on a more prosaic question, though arguably more relevant to Nvidia’s investors: Huang’s precarious position as its “single point of failure”. Both books portray Huang, now 62, as a solitary figure at the centre of his company.
After Jobs died, Sir Jony Ive and Tim Cook led Apple even further into the stratosphere. But which of Nvidia’s dozens of deputies can step in when Huang finally hangs up his leather jacket?